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Infant Imaging

Scientists at UNC-Chapel Hill are using MRI images to study the early development of the brain, and to discover potential early signs of autism.

CHAPEL HILL — You may not realize it, watching as a baby manipulates a small toy; and you probably don’t think about it while holding a toddler’s tiny hands as they learn to walk, but early childhood is the most rapid and dynamic period of brain development.

That’s because through play, manipulation and watching the surrounding world, a child is learning so much in a short period of time. But it turns out that brain growth is not uniform.

“Obviously when the brain grows from a small brain to a large brain, it’s not a proportional growth for the whole brain," says Lin Weili, Ph.D. and vice chair of basic research and radiology at the University of North Carolina School of Medicine. “Different parts of the brain have different trajectories, so some of the region grows faster and some grows slower. So it’s not proportional.”

The fastest developing areas of the brain coincide with skills the child is learning at that time, such as fine motor skills, walking and speech. The area grows because neural connections are being made.

It is only when you see 3D images of the brain, at six, 12 and 24 months, that the truly dramatic change is visible. The brain, and thus the child’s head, grows to almost 90 percent of an adult brain size in the first year.

Dr. John Gilmore, a professor of psychiatry at the University of North Carolina School of Medicine, explains as he points out the features on a side scan of a child’s head.

“So this is the baby’s eye and this is the brain inside the skull,” says Gilmore, as he runs his finger around the outline of the skull. “At the top of the brain is the cortical rim, or what is called the gray matter of the brain. This is where the neurons are, so that’s where the work of thinking and sensing happens.”

Just beneath that is what doctors call the white matter. It appears more gray in a baby’s brain, but it turns much more white by the time the child is around two years old.

“The white matter is the connections between the neurons,” Gilmore continues. “So if a neuron here wants to talk to a neuron there, it has to go through a long track that goes through the brain. And as more of those connections are made, this area becomes thicker and it turns into a brighter white. So if you compare a baby’s brain with the brain of a child that is two or three years old, it’s clear how many connections have been made.”

These discoveries stem from The Baby Connectome Project. The four-year study at the UNC-Chapel Hill School of Medicine aims to produce unprecedented information about early brain development from birth through early childhood as well as the factors contributing to a healthy brain.

“This screen shows the MRI of the same child taken every three months, starting at three months,” explains Dinggang Shen, Ph.D. and director of the Biomedical Research Imaging Center at the University of North Carolina School of Medicine. “You can clearly see that not only is the brain getting larger, but the gray matter is expanding to fill the skull but the white matter is also growing and getting whiter. So the child is learning and making connections.”

For the project, researchers are performing safe and non-invasive brain scans of 500 children aged zero to five years.

Gilmore says one of the first discoveries from the brain imaging is how much the child already knows at birth.

“It looks like, in the first year of life, the sensory motor regions of the brain, including the motor cortex and the visual cortex where we process visual information, is already more developed at birth and coming on line,” Gilmore says, pointing to the MRI of the infant. “But then in the first two years of life, the parts of the brain that control higher orders, that actually do the thinking and integrate information, develop rapidly.”

The project is unique. MRI’s or brain scans, have never been used in this way to try and understand, characterize and quantify the changes associated with the structure and function of the brain.

“So coupled with that, if a subject learns to walk, what part of the brain is actually responsible for all these behavior changes?” adds Lin, who believes researchers should be able to see the changes in the brain and also connect those changes to the behavior. “Or if a toddler starts to become more attached to the parents, which part of the brain is important for attachment?”

Scientists also hope that by identifying the factors that contribute to healthy brain development, they can learn how to predict whether infants at high risk will develop autism.

“There’s very good reason to think that we can eventually identify brain biomarkers that can help us predict who is going to get autism,” says Dr. Joe Piven, MD. and director of the Carolina Institute for Developmental Disabilities at the UNC School of Medicine. “And that opens up the door to intervention in the first year, which is the best time because the brain is much more amenable to change and much more plastic. It’s also a time before the onset of symptoms, which makes intervention much easier.”

Scientists are also using MRI Scans to study infants at higher risk for developing autism if they have an older sibling with the disease.

Piven points out that at six months, when a child who is going to end up with autism by age two or three is compared to a child who isn’t, there is no difference as far as the features of autism. That’s because autism doesn’t emerge until ages 18 months to two years.

“So you have to look at the changes in the brain that go from not having autism to having autism to really understand what is happening,” adds Piven. “And we now believe we are beginning to have evidence that we can predict in the first year of life, based on brain biomarkers and in kids who are at high risk because a sibling is autistic, those children who are going to develop autism.”

The imaging, all of the researchers say, is an essential tool that will move medicine forward towards coming up with a way to predict autism and create a targeted treatment.